Instructions to use yiyangd/vlm4vla-internvl3_5-1b-bridge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiyangd/vlm4vla-internvl3_5-1b-bridge with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yiyangd/vlm4vla-internvl3_5-1b-bridge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0087a56d6c7d8728876db5f52745e45bb143b57745b2fa2c8495050f7f7fee9
- Size of remote file:
- 2.12 GB
- SHA256:
- f57f341f07246ff797d67b288c2357546f9d4fd74dfba784bbd7b86273f50b24
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.